Data Engineer, Care Continuity

• 3–6+ years of experience in data engineering, building production data pipelines
• Strong experience with ETL pipeline development using modern tools (e.g., Airflow, dbt, Spark, etc.)
• Proficiency in Python, SQL, and NoSQL databases
• Experience working with HL7 CDA / CCD documents, FHIR resources, or other healthcare data formats
• Experience designing data models for analytics and machine learning
• Strong problem-solving mindset and willingness to dive into ambiguity

Desirable

• You'll be responsible for designing and implementing scalable, reliable ETL pipelines that power our core data platform
• You'll collaborate closely with product, data analytics, data science, and engineering to understand requirements and ensure data pipelines align with end-user needs. You'll also help shape our data infrastructure, build reusable transformation logic, and enforce best practices for data quality and governance
• This is a high-ownership role for someone excited to solve complex data problems at the intersection of healthcare, analytics, and product development
• Design scalable data models to support downstream analysis and reporting
• Create and optimize data pipelines for efficient data processing, ensuring data is readily available for data scientists and analysts
• Help define data engineering standards, tooling, and architecture as we scale
• Implement data quality checks, logging, and monitoring for reliability and transparency
• Collaborate with product, data analytics, and data science to translate requirements into robust data workflows
• Collaborate with engineering to define and implement ingestion across data sources
• Write clean, testable code for transformation logic and pipeline orchestration
• Produce clear documentation and runbooks